python main.py
    --env_name AntEnv
    --env_hook DominoHook
    --use_weighted_info_nce
    --adversarial_loss_coef 0.1
    --method OURSACFastAll
    --buffer_size 100000
    --encoder_eps_type all
    --train_freq 32
    --gradient_steps 32
    --learning_rate 1e-4
    --contrast_frame_stack 10
    --encoder_tau 0.05
    --seed 101
    --use_wandb
    --test_envs "[([0.4, 0.5], [0.4, 0.5]),([0.40, 0.50], [1.50, 1.60]),([1.50, 1.60], [0.40, 0.50]),([1.50, 1.60], [1.50, 1.60])]"
    --test_eps_num_per_env 10
    --train_envs "[([0.75,0.85], [0.75,0.85]),([0.75,0.85], [1.0,1.15,1.25]),([1.0,1.15,1.25], [0.75,0.85]),([1.0,1.15,1.25], [1.0,1.15,1.25])]" 
##
python main.py
    --env_name HalfCheetahEnv
    --env_hook DominoHook
    --use_weighted_info_nce
    --adversarial_loss_coef 0.1
    --method OURSACFastAll
    --buffer_size 100000
    --encoder_eps_type all
    --train_freq 32
    --gradient_steps 32
    --learning_rate 1e-4
    --contrast_frame_stack 10
    --encoder_tau 0.05
    --use_wandb
    --seed 101
    --test_envs "[([0.40, 0.50],[0.40, 0.50]),([0.40, 0.50],[1.50, 1.60]),([1.50, 1.60],[0.40, 0.50]),([1.50, 1.60],[1.50, 1.60])]"
    --test_eps_num_per_env 10
    --train_envs "[([0.75,0.85], [0.75,0.85]),([0.75,0.85], [1.0,1.15,1.25]),([1.0,1.15,1.25], [0.75,0.85]),([1.0,1.15,1.25], [1.0,1.15,1.25])]" 
##
python main.py
    --env_name CrippleAntEnv
    --env_hook DominoHook
    --use_weighted_info_nce
    --adversarial_loss_coef 0.1
    --method OURSACFastBase
    --buffer_size 100000
    --encoder_eps_type all
    --train_freq 32
    --gradient_steps 32
    --learning_rate 1e-4
    --contrast_frame_stack 10
    --encoder_tau 0.05
    --seed 101
    --use_wandb
    --test_envs "[([3], [0],[0.4, 0.5]),([3], [0],[1.5, 1.6])]"
    --test_eps_num_per_env 10
    --train_envs "[([0, 1], [0], [0.75,0.85]),([0, 1], [0], [0.75,0.85]),([2], [0], [0.75,0.85]),([2], [0], [1.0,1.15,1.25])]" 
##
python main.py
    --env_name CrippleHalfCheetahEnv
    --env_hook DominoHook
    --use_weighted_info_nce
    --adversarial_loss_coef 0.1
    --method OURSACFastAll
    --buffer_size 100000
    --encoder_eps_type all
    --train_freq 32
    --gradient_steps 32
    --learning_rate 1e-4
    --contrast_frame_stack 10
    --encoder_tau 0.05
    --use_wandb
    --seed 101
    --test_envs "[([4, 5], [0], [0.4, 0.5]),([4, 5], [0],[1.5, 1.6])]"
    --test_eps_num_per_env 10
    --train_envs "[([0, 1], [0], [0.75,0.85]),([0, 1], [0], [1.0,1.15,1.25]),([2, 3], [0], [0.75,0.85]),([2, 3], [0], [1.0,1.15,1.25])]" 
##
python main.py
    --env_name SlimHumanoidEnv
    --env_hook DominoHook
    --use_weighted_info_nce
    --adversarial_loss_coef 0.1
    --method OURSACFastAll
    --buffer_size 100000
    --encoder_eps_type all
    --train_freq 32
    --gradient_steps 32
    --learning_rate 1e-4
    --contrast_frame_stack 10
    --encoder_tau 0.05
    --seed 101
    --use_wandb
    --test_envs "[([0.60, 0.70], [0.60, 0.70]),([0.60, 0.70], [1.50, 1.60]),([1.50, 1.60], [0.60, 0.70]),([1.50, 1.60], [1.50, 1.60])]"
    --test_eps_num_per_env 10
    --train_envs "[([0.8, 0.9], [0.8, 0.9]),([0.8, 0.9], [1.0, 1.15, 1.25]),([1.0, 1.15, 1.25], [0.8, 0.9]),([1.0, 1.15, 1.25], [1.0, 1.15, 1.25])]" 

##
python main.py
    --env_name HopperEnv
    --env_hook DominoHook
    --use_weighted_info_nce
    --adversarial_loss_coef 0.1
    --method OURSACFastAll
    --buffer_size 100000
    --encoder_eps_type all
    --train_freq 32
    --gradient_steps 32
    --learning_rate 1e-4
    --contrast_frame_stack 10
    --encoder_tau 0.05
    --seed 101
    --test_envs "[([0.25, 0.375], [0.25, 0.375]),([0.25, 0.375], [1.75, 2.0]),([1.75, 2.0], [0.25, 0.375]),([1.75, 2.0], [1.75, 2.0])]"
    --test_eps_num_per_env 10
    --use_wandb
    --train_envs "[([0.5, 0.75, 1.0], [0.5, 0.75, 1.0]),([0.5, 0.75, 1.0], [1.25, 1.5]),([1.25, 1.5], [0.5, 0.75, 1.0]),([1.25, 1.5], [1.25, 1.5])]" 

